Forecasting Malaysian Gold Using. GARCH Model

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Forecasting Malaysian Gold Using. GARCH Model"

Transcription

1 Applied Mahemaical Sciences, Vol. 7, 2013, no. 58, HIKARI Ld, Forecasing Malaysian Gold Using GARCH Model Pung Yean Ping 1, Nor Hamizah Miswan 2 and Maizah Hura Ahmad 3 Deparmen of Mahemaical Sciences, Faculy of Science, Universii Teknologi Malaysia, UTM Skudai, Johor, Malaysia Copyrigh 2013 Pung Yean Ping e al. This is an open access aricle disribued under he Creaive Commons Aribuion License, which permis unresriced use, disribuion, and reproducion in any medium, provided he original work is properly cied. Absrac The purpose of he curren sudy is o forecas he prices of Kijang Emas, he official Malaysian gold bullion. Two mehods are considered, which are Box-Jenkins Auoregressive Inegraed Moving Average (ARIMA) and Generalized Auoregressive Condiional Heeroskedasiciy (GARCH). Using Akaike's informaion crierion (AIC) as he goodness of fi measure and mean absolue percenage error (MAPE) as he forecasing performance measure, he sudy concludes ha GARCH is a more appropriae model. Analysis are carried ou by using he E-views sofware. Keywords: Box-Jenkins Auoregressive Inegraed Moving Average (ARIMA), Generalized Auoregressive Condiional Heeroskedasiciy (GARCH), volailiy 1 Inroducion One goal of ime series analysis is o forecas he fuure values of he ime series daa. In he case of Kijang Emas, he official Malaysian gold bullion coin, he forecasing of is prices is useful for invesmen purposes in Malaysia. Nor Hamizah Miswan e al. [1] developed Box-Jenkins Auoregressive Inegraed Moving Average (ARIMA) model o forecas Kijang Emas prices. Kijang emas prices however are volaile wih huge price swings. Volailiy is a condiion where he condiional variance changes beween exremely high and low values. In he lieraure, when dealing wih such series, he emphasis has been given on forecasing he volailiy or he ime-varying condiional variance of he

2 2880 Pung Yean Ping e al. series. The ARCH class of models, pioneered by Engle in 1982 and generalized by Bollerslev in 1986 are popular class of economeric models for describing a series wih ime-varying condiional variance [2]. The Generalized Auoregressive Condiional Heeroskedasiciy (GARCH) family models were developed o capure volailiy clusering or he periods of flucuaions, and predic volailiies in he fuure [3]. Seing Box-Jenkins ARIMA as he benchmark model, he curren sudy forecas Kijang Emas prices using GARCH model. By using he E-views sofware, he GARCH model is used o provide a volailiy clusering measure of he gold series. The goodness of fi and he forecasing performances of hese models are measured by Akaike's informaion crierion (AIC) and mean absolue percenage error (MAPE) respecively. 2 Mehodology The mehods ha are used in he curren sudy are Box-Jenkins ARIMA and GARCH where he former is used as a benchmark model. The daa used are Malaysian gold prices ha are non-saionary in naure. Box-Jenkins ARIMA To apply he Box-Jenkins ARIMA procedures o such ime series, he series need o be reduced o saionariy by aking a proper degree of differencing. This resuls in a model denoed by ARIMA (p,d,) where p is he auoregressive order, is he moving average order and d is he order of differences. The ARIMA(p,d,) can be wrien as d ( B )(1 B) y ( B) a where p p p ( B) 11B... pb is he auoregressive operaor of order p; ( B) 11 B... B is he moving average operaor of order; (1B) d is he d h difference; B is backward shif operaor; and a is he error erm a ime. GARCH The GARCH model on he oher hand, has he abiliy o model ime-varying condiional variances. The model uses pas variances and pas variance forecass o forecas fuure variances. The GARCH (p, ) model is

3 Forecasing Malaysian gold using GARCH model 2881 where u 2 h, ~ N(0,1) where,, for saionariy; p is he order of he GARCH erms 2, which is he las period forecas variance. is he order of he ARCH erms 2, which is he informaion abou volailiy from he previous period measured as he lag of suared residual from he mean euaion. Akaike Informaion Crierion (AIC) AIC is a echniue for selecing a model from a se of models o measure he goodness of fi of an esimaed saisical model. I is based on informaion heory and is a crierion ha seeks a model which has a good fi o he ruh bu few parameers. The model is chosen by minimizing he Kullback-Leibler disance beween he model and he ruh. AIC is compued as follows: AIC 2 ln 2k where is he maximized value of he likelihood funcion for he esimaed model; k is he number of free and independen parameers in he model. From several models of a given daa se, he bes model is he one which has he lowes AIC value. Forecas Accuracy Measure There are several measures for evaluaing forecass. For he curren sudy, he mean absolue percenage error (MAPE) will be calculaed. MAPE measures he accuracy of forecas in erms of percenage. The formula is as follows: n ˆ MAPE = y y / 100% n 1 y where is he acual value; is he forecas value; n is he number of periods. In comparing he performances beween wo models, he smaller he value of MAPE, he beer he model is. 3 Daa Analysis and Resuls Figure 1 plos he daily Kijang Emas prices recorded from18 July 2001 unil 25 Sepember 2012 ha are used in he sudy.

4 2882 Pung Yean Ping e al. Figure 1: Daily Kijang Emas Prices from 18 July 2001 unil 25 Sepember 2012 Trend is apparen from he plo, indicaing he necessiy for ransformaion and differencing o make he series saionary. Box-Cox ransformaion was firs applied, followed by aking he firs difference of he daa. Figure 2 illusraes he firs difference of he ransformed series. Figure 2: Firs Difference of Transformed Kijang Emas To idenify he model, he auocorrelaion funcion (ACF) and parial auocorrelaion funcion (PACF) of he ransformed daa are ploed in Figure 3.

5 Forecasing Malaysian gold using GARCH model 2883 Figure 3: ACF and PACF for Transformed Kijang Emas As idenified by Nor Hamizah Miswan e al. [1], he mos appropriae ARIMA model for his series is ARIMA(1,1,1) wih an AIC value of and forecasing error of For he GARCH analysis, he esing of saionariy was followed by he esing of volailiy. The rend ha affeced he non-saionariy of he series was firs removed by aking he firs difference of he series resuling in a series as ploed in Figure 4, wih he volailiy cluserings circled. Figure 4: Volailiy Clusering for he Differenced Kijang Emas

6 2884 Pung Yean Ping e al. Model idenificaion of he GARCH model is based on he ACF and PACF plos. GARCH (1, 1) was developed where he parameers of he model were esimaed by using maximum likelihood esimaion (MLE). Engle, he developer of ARCH and Bollerslev, he developer of GARCH have proven ha MLE was he bes esimaion mehod for hese models. The esimaes for GARCH (1, 1) model are = , 0 = 2.95E-06, 1 = and 1 = The values of mean euaions are small and posiive indicaing significan parameers. These saisfy he posiiviy consrain of GARCH model. The value of 0 1 1is less han bu close o uniy and This indicaes ha volailiy shocks are uie persisen. The coefficien of he lagged suared reurns is posiive and saisically significan indicaing ha srong GARCH effecs are apparen for he gold marke. Also, he coefficien of lagged condiional variance is significanly posiive and less han one indicaing ha he impac of old news on volailiy is significan. Higher value of indicaes a long memory in he 1 variance. The AIC value for his model is wih a forecasing error of Conclusion The kijang emas prices daa considered in he curren sudy can be characerized by GARCH (1, 1) model. Based on a lower SIC value, GARCH (1, 1) is more appropriae han ARIMA (1, 1, 1) in forecasing is fuure values. The lower value of MAPE for GARCH (1, 1) when compared o ha of ARIMA (1, 1, 1) showed ha GARCH (1, 1) is he more appropriae model. Acknowledgemen This sudy was suppored by Universii Teknologi Malaysia and he Minisry of Higher Educaion (MOHE), Malaysia. References [1] Nor Hamizah Miswan, Pung Yean Ping and Maizah Hura Ahmad, On Parameer Esimaion for Malaysian Gold Prices Modelling and Forecasing, Inernaional Journal of Mahemaical Analysis, 7 (22), 2013, [2] R. F. Engle, An Inroducion o he Use of ARCH/GARCH models in Applied Economerics, Journal of Business, New York (1982). [3] T. Bollerslev, Generalized Auoregressive Condiional Heeroskedasiciy, Journal of Economerics, 31, 1986, Received: March 11, 2013

An empirical analysis about forecasting Tmall air-conditioning sales using time series model Yan Xia

An empirical analysis about forecasting Tmall air-conditioning sales using time series model Yan Xia An empirical analysis abou forecasing Tmall air-condiioning sales using ime series model Yan Xia Deparmen of Mahemaics, Ocean Universiy of China, China Absrac Time series model is a hospo in he research

More information

Time Series Modeling for Risk of Stock. Price with Value at Risk Computation

Time Series Modeling for Risk of Stock. Price with Value at Risk Computation Applied Mahemaical Sciences, Vol 9, 015, no 56, 779-787 HIKARI Ld, wwwm-hikaricom hp://dxdoiorg/101988/ams0155144 Time Series Modeling for Risk of Sock Price wih Value a Risk Compuaion Dodi Deviano, Maiyasri

More information

DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR

DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR Invesmen Managemen and Financial Innovaions, Volume 4, Issue 3, 7 33 DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR Ahanasios

More information

Impact of Debt on Primary Deficit and GSDP Gap in Odisha: Empirical Evidences

Impact of Debt on Primary Deficit and GSDP Gap in Odisha: Empirical Evidences S.R. No. 002 10/2015/CEFT Impac of Deb on Primary Defici and GSDP Gap in Odisha: Empirical Evidences 1. Inroducion The excessive pressure of public expendiure over is revenue receip is financed hrough

More information

Cointegration Analysis of Exchange Rate in Foreign Exchange Market

Cointegration Analysis of Exchange Rate in Foreign Exchange Market Coinegraion Analysis of Exchange Rae in Foreign Exchange Marke Wang Jian, Wang Shu-li School of Economics, Wuhan Universiy of Technology, P.R.China, 430074 Absrac: This paper educed ha he series of exchange

More information

Stock Price Prediction Using the ARIMA Model

Stock Price Prediction Using the ARIMA Model 2014 UKSim-AMSS 16h Inernaional Conference on Compuer Modelling and Simulaion Sock Price Predicion Using he ARIMA Model 1 Ayodele A. Adebiyi., 2 Aderemi O. Adewumi 1,2 School of Mahemaic, Saisics & Compuer

More information

FORECASTING THE UK UNEMPLOYMENT RATE: MODEL COMPARISONS FLOROS, Christos *

FORECASTING THE UK UNEMPLOYMENT RATE: MODEL COMPARISONS FLOROS, Christos * Inernaional Journal of Applied Economerics and Quaniaive Sudies. Vol.-(005) FORECASTING THE UK UNEMPLOYMENT RATE: MODEL COMPARISONS FLOROS, Chrisos * Absrac This paper compares he ou-of-sample forecasing

More information

Vector Autoregressions (VARs): Operational Perspectives

Vector Autoregressions (VARs): Operational Perspectives Vecor Auoregressions (VARs): Operaional Perspecives Primary Source: Sock, James H., and Mark W. Wason, Vecor Auoregressions, Journal of Economic Perspecives, Vol. 15 No. 4 (Fall 2001), 101-115. Macroeconomericians

More information

Usefulness of the Forward Curve in Forecasting Oil Prices

Usefulness of the Forward Curve in Forecasting Oil Prices Usefulness of he Forward Curve in Forecasing Oil Prices Akira Yanagisawa Leader Energy Demand, Supply and Forecas Analysis Group The Energy Daa and Modelling Cener Summary When people analyse oil prices,

More information

Forecasting Electricity Consumption for Pakistan

Forecasting Electricity Consumption for Pakistan Websie: www.ijeae.com (ISSN 50-459, ISO 9001:008 Cerified Journal, Volume 4, Issue 4, April 014) Forecasing Elecriciy Consumpion for Pakisan Absrac Now-a-days, differen secors of he economy are being significanly

More information

Economic Factors in Determining the Penetration Coefficient of Mobile Phone in Iran

Economic Factors in Determining the Penetration Coefficient of Mobile Phone in Iran Iranian Economic Review, Vol.5, No.26, Spring 200 Economic Facors in Deermining he Peneraion Coefficien of Mobile Phone in Iran Mansour Khalili Araghi Ghahreman Abdoli Absrac n his paper we have sudied

More information

Chapter 8: Regression with Lagged Explanatory Variables

Chapter 8: Regression with Lagged Explanatory Variables Chaper 8: Regression wih Lagged Explanaory Variables Time series daa: Y for =1,..,T End goal: Regression model relaing a dependen variable o explanaory variables. Wih ime series new issues arise: 1. One

More information

Modeling the Causal Effect of World Cocoa Price on Production of Cocoa in Ghana

Modeling the Causal Effect of World Cocoa Price on Production of Cocoa in Ghana Universal Journal of Agriculural Research 2(7): 264-271, 2014 DOI: 10.13189/ujar.2014.020706 hp://www.hrpub.org Modeling he Causal Effec of World Cocoa Price on Producion of Cocoa in Ghana Sampson Ankrah

More information

Improvement in Forecasting Accuracy Using the Hybrid Model of ARFIMA and Feed Forward Neural Network

Improvement in Forecasting Accuracy Using the Hybrid Model of ARFIMA and Feed Forward Neural Network American Journal of Inelligen Sysems 2012, 2(2): 12-17 DOI: 10.5923/j.ajis.20120202.02 Improvemen in Forecasing Accuracy Using he Hybrid Model of ARFIMA and Feed Forward Neural Nework Cagdas Hakan Aladag

More information

Are GARCH Specifications Superior Among GARCH Types of Models in Estimating Financial Volatility?: An Experiment

Are GARCH Specifications Superior Among GARCH Types of Models in Estimating Financial Volatility?: An Experiment Srivasava e. al, Aeeay - Journal of Managemen Sciences And Technology (1), Feb - 014 ISSN -347-5005 Are GARCH Secificaions Suerior Among GARCH Tyes of Models in Esimaing Financial Volailiy?: An Exerimen

More information

Issues Using OLS with Time Series Data. Time series data NOT randomly sampled in same way as cross sectional each obs not i.i.d

Issues Using OLS with Time Series Data. Time series data NOT randomly sampled in same way as cross sectional each obs not i.i.d These noes largely concern auocorrelaion Issues Using OLS wih Time Series Daa Recall main poins from Chaper 10: Time series daa NOT randomly sampled in same way as cross secional each obs no i.i.d Why?

More information

SPEC model selection algorithm for ARCH models: an options pricing evaluation framework

SPEC model selection algorithm for ARCH models: an options pricing evaluation framework Applied Financial Economics Leers, 2008, 4, 419 423 SEC model selecion algorihm for ARCH models: an opions pricing evaluaion framework Savros Degiannakis a, * and Evdokia Xekalaki a,b a Deparmen of Saisics,

More information

Key Words: Steel Modelling, ARMA, GARCH, COGARCH, Lévy Processes, Discrete Time Models, Continuous Time Models, Stochastic Modelling

Key Words: Steel Modelling, ARMA, GARCH, COGARCH, Lévy Processes, Discrete Time Models, Continuous Time Models, Stochastic Modelling Vol 4, No, 01 ISSN: 1309-8055 (Online STEEL PRICE MODELLING WITH LEVY PROCESS Emre Kahraman Türk Ekonomi Bankası (TEB A.Ş. Direcor / Risk Capial Markes Deparmen emre.kahraman@eb.com.r Gazanfer Unal Yediepe

More information

INVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS

INVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS INVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS Ilona Tregub, Olga Filina, Irina Kondakova Financial Universiy under he Governmen of he Russian Federaion 1. Phillips curve In economics,

More information

How Useful are the Various Volatility Estimators for Improving GARCH-based Volatility Forecasts? Evidence from the Nasdaq-100 Stock Index

How Useful are the Various Volatility Estimators for Improving GARCH-based Volatility Forecasts? Evidence from the Nasdaq-100 Stock Index Inernaional Journal of Economics and Financial Issues Vol. 4, No. 3, 04, pp.65-656 ISSN: 46-438 www.econjournals.com How Useful are he Various Volailiy Esimaors for Improving GARCH-based Volailiy Forecass?

More information

Demand and Price Forecasting Models for Strategic and Planning Decisions in a Supply Chain

Demand and Price Forecasting Models for Strategic and Planning Decisions in a Supply Chain Proc. Schl. ITE Tokai Univ. vol.3,no,,pp.37-4 Vol.,No.,,pp. - Paper Demand and Price Forecasing Models for Sraegic and Planning Decisions in a Supply Chain by Vichuda WATTANARAT *, Phounsakda PHIMPHAVONG

More information

MODELING TO ANTICIPATE WORLD PRICE OF EACH OUNCE OF GOLD IN INTERNATIONAL MARKETS

MODELING TO ANTICIPATE WORLD PRICE OF EACH OUNCE OF GOLD IN INTERNATIONAL MARKETS Vol. No.2, pp.-, June 203 MODELING TO ANTICIPATE WORLD PRICE OF EACH OUNCE OF GOLD IN INTERNATIONAL MARKETS Mohammad Rikhegar Business Managemen, MA Suden Islamic Azad Universiy, a Souh Tehran Branch 009893632406

More information

Strictly as per the compliance and regulations of:

Strictly as per the compliance and regulations of: Global Journal of Managemen and Business Research Finance Volume 3 Issue 3 Version.0 Year 03 Type: Double Blind Peer Reviewed Inernaional Research Journal Publisher: Global Journals Inc. (USA) Online ISSN:

More information

Forecasting Electricity Consumption: A Comparison of Models for New Zealand

Forecasting Electricity Consumption: A Comparison of Models for New Zealand Paper Tile: Forecasing Elecriciy Consumpion: A Comparison of Models for New Zealand Auhors: Zaid Mohamed and Pa Bodger,* Affiliaions:. Mohamed, Z., B.E (Hons), is a Ph.D. suden in he Deparmen of Elecrical

More information

Part 1: White Noise and Moving Average Models

Part 1: White Noise and Moving Average Models Chaper 3: Forecasing From Time Series Models Par 1: Whie Noise and Moving Average Models Saionariy In his chaper, we sudy models for saionary ime series. A ime series is saionary if is underlying saisical

More information

Advanced time-series analysis (University of Lund, Economic History Department)

Advanced time-series analysis (University of Lund, Economic History Department) Advanced ime-series analysis (Universiy of Lund, Economic Hisory Deparmen) 30 Jan-3 February and 6-30 March 01 Lecure Uni-roo esing and he consequences of non-saionariy on regression analysis..a. Why is

More information

DYNAMIC ECONOMETRIC MODELS Vol. 7 Nicolaus Copernicus University Toruń 2006. Ryszard Doman Adam Mickiewicz University in Poznań

DYNAMIC ECONOMETRIC MODELS Vol. 7 Nicolaus Copernicus University Toruń 2006. Ryszard Doman Adam Mickiewicz University in Poznań DYNAMIC ECONOMETRIC MODELS Vol. 7 Nicolaus Copernicus Universiy Toruń 26 1. Inroducion Adam Mickiewicz Universiy in Poznań Measuring Condiional Dependence of Polish Financial Reurns Idenificaion of condiional

More information

Chapter 8 Student Lecture Notes 8-1

Chapter 8 Student Lecture Notes 8-1 Chaper Suden Lecure Noes - Chaper Goals QM: Business Saisics Chaper Analyzing and Forecasing -Series Daa Afer compleing his chaper, you should be able o: Idenify he componens presen in a ime series Develop

More information

Time Series Analysis Using SAS R Part I The Augmented Dickey-Fuller (ADF) Test

Time Series Analysis Using SAS R Part I The Augmented Dickey-Fuller (ADF) Test ABSTRACT Time Series Analysis Using SAS R Par I The Augmened Dickey-Fuller (ADF) Tes By Ismail E. Mohamed The purpose of his series of aricles is o discuss SAS programming echniques specifically designed

More information

Purchasing Power Parity (PPP), Sweden before and after EURO times

Purchasing Power Parity (PPP), Sweden before and after EURO times School of Economics and Managemen Purchasing Power Pariy (PPP), Sweden before and afer EURO imes - Uni Roo Tes - Coinegraion Tes Masers hesis in Saisics - Spring 2008 Auhors: Mansoor, Rashid Smora, Ami

More information

The Relationship between Stock Return Volatility and. Trading Volume: The case of The Philippines*

The Relationship between Stock Return Volatility and. Trading Volume: The case of The Philippines* The Relaionship beween Sock Reurn Volailiy and Trading Volume: The case of The Philippines* Manabu Asai Faculy of Economics Soka Universiy Angelo Unie Economics Deparmen De La Salle Universiy Manila May

More information

Principal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya.

Principal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya. Principal componens of sock marke dynamics Mehodology and applicaions in brief o be updaed Andrei Bouzaev, bouzaev@ya.ru Why principal componens are needed Objecives undersand he evidence of more han one

More information

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005

Measuring macroeconomic volatility Applications to export revenue data, 1970-2005 FONDATION POUR LES ETUDES ET RERS LE DEVELOPPEMENT INTERNATIONAL Measuring macroeconomic volailiy Applicaions o expor revenue daa, 1970-005 by Joël Cariolle Policy brief no. 47 March 01 The FERDI is a

More information

The naive method discussed in Lecture 1 uses the most recent observations to forecast future values. That is, Y ˆ t + 1

The naive method discussed in Lecture 1 uses the most recent observations to forecast future values. That is, Y ˆ t + 1 Business Condiions & Forecasing Exponenial Smoohing LECTURE 2 MOVING AVERAGES AND EXPONENTIAL SMOOTHING OVERVIEW This lecure inroduces ime-series smoohing forecasing mehods. Various models are discussed,

More information

Government Revenue Forecasting in Nepal

Government Revenue Forecasting in Nepal Governmen Revenue Forecasing in Nepal T. P. Koirala, Ph.D.* Absrac This paper aemps o idenify appropriae mehods for governmen revenues forecasing based on ime series forecasing. I have uilized level daa

More information

Time Series Analysis for Predicting the Occurrences of Large Scale Earthquakes

Time Series Analysis for Predicting the Occurrences of Large Scale Earthquakes Inernaional Journal of Applied Science and Technology Vol. No. 7; Augus 01 Time Series Analysis for Predicing he Occurrences of Large Scale Earhquakes Amei Amei* Wandong Fu** Chih-Hsiang Ho*** Absrac Earhquakes

More information

A DCC Analysis of Two Stock Market Returns Volatility with an Oil Price Factor: An Evidence Study of Singapore and Thailand s Stock Markets

A DCC Analysis of Two Stock Market Returns Volatility with an Oil Price Factor: An Evidence Study of Singapore and Thailand s Stock Markets Journal of Convergence Informaion Technology Volume 4, Number 1, March 9 A DCC Analysis of Two Sock Marke Reurns Volailiy wih an Oil Price Facor: An Evidence Sudy of Singapore and Thailand s Sock Markes

More information

An Empirical Investigation of the Monetary Model Economic Fundamentals

An Empirical Investigation of the Monetary Model Economic Fundamentals Modern Economy, 06, 7, 78-740 hp://www.scirp.org/ournal/me ISSN Online: 5-76 ISSN Prin: 5-745 An Empirical Invesigaion of he Moneary Model Economic Fundamenals Jean René Cupidon, Judex Hyppolie Deparmen

More information

A Note on Renewal Theory for T -iid Random Fuzzy Variables

A Note on Renewal Theory for T -iid Random Fuzzy Variables Applied Mahemaical Sciences, Vol, 6, no 6, 97-979 HIKARI Ld, wwwm-hikaricom hp://dxdoiorg/988/ams6686 A Noe on Renewal Theory for T -iid Rom Fuzzy Variables Dug Hun Hong Deparmen of Mahemaics, Myongji

More information

Value at Risk part II. Weighted Historical Simulation. BRW Approach. HW Approach

Value at Risk part II. Weighted Historical Simulation. BRW Approach. HW Approach Value a Risk par II Weighed Hisorical Simulaion Chuang I - Yuan Deparmen of Finance, NCCU Weighed Hisorical Simulaion 3 BRW Approach 4 Boudoukh, Richardson and Whielaw (Risk, 998) Hull and Whie (JR, 998)

More information

COMPUTATION OF CENTILES AND Z-SCORES FOR HEIGHT-FOR-AGE, WEIGHT-FOR-AGE AND BMI-FOR-AGE

COMPUTATION OF CENTILES AND Z-SCORES FOR HEIGHT-FOR-AGE, WEIGHT-FOR-AGE AND BMI-FOR-AGE COMPUTATION OF CENTILES AND Z-SCORES FOR HEIGHT-FOR-AGE, WEIGHT-FOR-AGE AND BMI-FOR-AGE The mehod used o consruc he 2007 WHO references relied on GAMLSS wih he Box-Cox power exponenial disribuion (Rigby

More information

Hotel Room Demand Forecasting via Observed Reservation Information

Hotel Room Demand Forecasting via Observed Reservation Information Proceedings of he Asia Pacific Indusrial Engineering & Managemen Sysems Conference 0 V. Kachivichyanuul, H.T. Luong, and R. Piaaso Eds. Hoel Room Demand Forecasing via Observed Reservaion Informaion aragain

More information

Modeling Long Memory in The Indian Stock Market using Fractionally Integrated Egarch Model

Modeling Long Memory in The Indian Stock Market using Fractionally Integrated Egarch Model Inernaional Journal of Trade, Economics and Finance, Vol., No.3, Ocober, 00 ing Long Memory in The Indian Sock Marke using Fracionally Inegraed Egarch Hojaallah Goudarzi Absrac The weak form of marke efficiency

More information

Oil Price Fluctuations and Firm Performance in an Emerging Market: Assessing Volatility and Asymmetric Effect

Oil Price Fluctuations and Firm Performance in an Emerging Market: Assessing Volatility and Asymmetric Effect Journal of Economics, Business and Managemen, Vol., No. 4, November 203 Oil Price Flucuaions and Firm Performance in an Emerging Marke: Assessing Volailiy and Asymmeric Effec Hawai Janor, Aisyah Abdul-Rahman,

More information

SAMUELSON S HYPOTHESIS IN GREEK STOCK INDEX FUTURES MARKET

SAMUELSON S HYPOTHESIS IN GREEK STOCK INDEX FUTURES MARKET 154 Invesmen Managemen and Financial Innovaions, Volume 3, Issue 2, 2006 SAMUELSON S HYPOTHESIS IN GREEK STOCK INDEX FUTURES MARKET Chrisos Floros, Dimirios V. Vougas Absrac Samuelson (1965) argues ha

More information

(Received June 17, 2004)

(Received June 17, 2004) TRANSPORTATION THE MALAYSIAN GOVERNMENT S ROAD ACCIDENT DEATH REDUCTION TARGET FOR YEAR 200 LAW, T.H. RADIN UMAR, R.S. WONG, S.V. Road Safey Research Cener Professor, Road Safey Research Cener Mechanical

More information

Modeling Tourist Arrivals Using Time Series Analysis: Evidence From Australia

Modeling Tourist Arrivals Using Time Series Analysis: Evidence From Australia Journal of Mahemaics and Saisics 8 (3): 348-360, 2012 ISSN 1549-3644 2012 Science Publicaions Modeling Touris Arrivals Using Time Series Analysis: Evidence From Ausralia 1 Gurudeo AnandTularam, 2 Vicor

More information

Cointegration: The Engle and Granger approach

Cointegration: The Engle and Granger approach Coinegraion: The Engle and Granger approach Inroducion Generally one would find mos of he economic variables o be non-saionary I(1) variables. Hence, any equilibrium heories ha involve hese variables require

More information

[web:reg] ARMA Excel Add-In

[web:reg] ARMA Excel Add-In [web:reg] ARMA Ecel Add-In [web:reg] Kur Annen www.web-reg.de annen@web-reg.de Körner Sr. 30 41464 Neuss - Germany - [web:reg] arma Ecel Add-In [web:reg] ARMA Ecel Add-In is a XLL for esimaing and forecas

More information

Lecture 18. Serial correlation: testing and estimation. Testing for serial correlation

Lecture 18. Serial correlation: testing and estimation. Testing for serial correlation Lecure 8. Serial correlaion: esing and esimaion Tesing for serial correlaion In lecure 6 we used graphical mehods o look for serial/auocorrelaion in he random error erm u. Because we canno observe he u

More information

THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES

THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES Juan Ángel Lafuene Universidad Jaume I Unidad Predeparamenal de Finanzas y Conabilidad Campus del Riu Sec. 1080, Casellón

More information

Lecture 12 Assumption Violation: Autocorrelation

Lecture 12 Assumption Violation: Autocorrelation Major Topics: Definiion Lecure 1 Assumpion Violaion: Auocorrelaion Daa Relaionship Represenaion Problem Deecion Remedy Page 1.1 Our Usual Roadmap Parial View Expansion of Esimae and Tes Model Sep Analyze

More information

ARIMA Models on Forecasting Sri Lankan Share Market Returns

ARIMA Models on Forecasting Sri Lankan Share Market Returns ISSN 2394-965 Vol. 2, Issue, pp: (6-2), Monh: January - April 5, Available a: www.novelyjournals.com Models on Forecasing Sri Lankan Share Marke Reurns W.G. S. Konarasinghe, 2 N. R. Abeynayake, 3 L.H.P.Gunarane

More information

Journal Of Business & Economics Research September 2005 Volume 3, Number 9

Journal Of Business & Economics Research September 2005 Volume 3, Number 9 Opion Pricing And Mone Carlo Simulaions George M. Jabbour, (Email: jabbour@gwu.edu), George Washingon Universiy Yi-Kang Liu, (yikang@gwu.edu), George Washingon Universiy ABSTRACT The advanage of Mone Carlo

More information

Modelling and Forecasting Volatility of Gold Price with Other Precious Metals Prices by Univariate GARCH Models

Modelling and Forecasting Volatility of Gold Price with Other Precious Metals Prices by Univariate GARCH Models Deparmen of Saisics Maser's Thesis Modelling and Forecasing Volailiy of Gold Price wih Oher Precious Meals Prices by Univariae GARCH Models Yuchen Du 1 Supervisor: Lars Forsberg 1 Yuchen.Du.84@suden.uu.se

More information

GARCH-Type modeling of stock market returns for the pre crisis. countries

GARCH-Type modeling of stock market returns for the pre crisis. countries July 21, Vol.6, No.7 (Serial No.62) Journal of Modern Accouning and Audiing, ISSN 1548-6583, USA GARCH-Type modeling of sock marke reurns for he pre crisis counries Erhan Demireli (Faculy of Economics

More information

A COMPARISON OF FORECASTING MODELS FOR ASEAN EQUITY MARKETS

A COMPARISON OF FORECASTING MODELS FOR ASEAN EQUITY MARKETS Sunway Academic Journal, 1 1 (005) A COMPARISON OF FORECASTING MODELS FOR ASEAN EQUITY MARKETS WONG YOKE CHEN a Sunway Universiy College KOK KIM LIAN b Universiy of Malaya ABSTRACT This paper compares

More information

The predictive power of volatility models: evidence from the ETF market

The predictive power of volatility models: evidence from the ETF market Invesmen Managemen and Financial Innovaions, Volume, Issue, 4 Chang-Wen Duan (Taiwan), Jung-Chu Lin (Taiwan) The predicive power of volailiy models: evidence from he ETF marke Absrac This sudy uses exchange-raded

More information

PARAMETRIC EXTREME VAR WITH LONG-RUN VOLATILITY: COMPARING OIL AND GAS COMPANIES OF BRAZIL AND USA.

PARAMETRIC EXTREME VAR WITH LONG-RUN VOLATILITY: COMPARING OIL AND GAS COMPANIES OF BRAZIL AND USA. Perspecivas Globais para a Engenharia de Produção Foraleza, CE, Brasil, 13 a 16 de ouubro de 015. PARAMETRIC EXTREME VAR WITH LONG-RUN VOLATILITY: COMPARING OIL AND GAS COMPANIES OF BRAZIL AND USA. RICARDO

More information

House Price Index (HPI)

House Price Index (HPI) House Price Index (HPI) The price index of second hand houses in Colombia (HPI), regisers annually and quarerly he evoluion of prices of his ype of dwelling. The calculaion is based on he repeaed sales

More information

Predicting Stock Market Index Trading Signals Using Neural Networks

Predicting Stock Market Index Trading Signals Using Neural Networks Predicing Sock Marke Index Trading Using Neural Neworks C. D. Tilakarane, S. A. Morris, M. A. Mammadov, C. P. Hurs Cenre for Informaics and Applied Opimizaion School of Informaion Technology and Mahemaical

More information

Social Media Content on Financial Markets

Social Media Content on Financial Markets Inernaional Journal of New Technology and Research (IJNTR) ISSN:2454-4116, Volume-2, Issue-3, March 2016 Pages 134-137 Social Media Conen on Financial Markes Juheng Zhang Absrac Socks are weeed by invesors

More information

Why Do Real and Nominal. Inventory-Sales Ratios Have Different Trends?

Why Do Real and Nominal. Inventory-Sales Ratios Have Different Trends? Why Do Real and Nominal Invenory-Sales Raios Have Differen Trends? By Valerie A. Ramey Professor of Economics Deparmen of Economics Universiy of California, San Diego and Research Associae Naional Bureau

More information

Chapter 7: Estimating the Variance of an Estimate s Probability Distribution

Chapter 7: Estimating the Variance of an Estimate s Probability Distribution Chaper 7: Esimaing he Variance of an Esimae s Probabiliy Disribuion Chaper 7 Ouline Review o Clin s Assignmen o General Properies of he Ordinary Leas Squares (OLS) Esimaion Procedure o Imporance of he

More information

Kernfachkombinationen: Investmentanalyse. Portfoliomanagement (Volatility Prediction)

Kernfachkombinationen: Investmentanalyse. Portfoliomanagement (Volatility Prediction) Kernfachkombinaionen: Invesmenanalyse Porfoliomanagemen (Volailiy Predicion) O. Univ.-Prof. Dr. Engelber J. Dockner Insiu für Beriebswirschafslehre Universiä Wien A-0 Brünnersrasse 7 Tel.: [43] () 477-3805

More information

Measuring the Downside Risk of the Exchange-Traded Funds: Do the Volatility Estimators Matter?

Measuring the Downside Risk of the Exchange-Traded Funds: Do the Volatility Estimators Matter? Proceedings of he Firs European Academic Research Conference on Global Business, Economics, Finance and Social Sciences (EAR5Ialy Conference) ISBN: 978--6345-028-6 Milan-Ialy, June 30-July -2, 205, Paper

More information

Inflation, exchange rates and interest rates in Ghana: An autoregressive distributed lag model

Inflation, exchange rates and interest rates in Ghana: An autoregressive distributed lag model Inernaional Journal of Scienific and Research Publicaions, Volume 5, Issue 1, January 215 1 ISSN 225-3153 Inflaion, exchange raes and ineres raes in Ghana: An auoregressive disribued lag model Dennis Nchor*,

More information

The 2012 US Presidential Election Polls. And Stock Returns

The 2012 US Presidential Election Polls. And Stock Returns Business and Economic esearch ISSN 6-4860 05, Vol. 5, No. The 0 US Presidenial Elecion Polls And Sock eurns Tamir Levy Neanya Academic College, Israel E-mail: leviami@neanya.ac.il Joseph Yagil Haifa Universiy

More information

Comparing Multivariate GARCH Models by Problem Dimension

Comparing Multivariate GARCH Models by Problem Dimension Comparing Mulivariae GARCH Models by Problem Dimension Massimiliano Caporin and Michael McAleer Absrac In he las 5 years, several Mulivariae GARCH (MGARCH) models have appeared in he lieraure. The wo mos

More information

A comparison of the Lee-Carter model and AR-ARCH model for forecasting mortality rates

A comparison of the Lee-Carter model and AR-ARCH model for forecasting mortality rates A comparison of he Lee-Carer model and AR-ARCH model for forecasing moraliy raes Rosella Giacomei a, Marida Berocchi b, Svelozar T. Rachev c, Frank J. Fabozzi d,e a Rosella Giacomei Deparmen of Mahemaics,

More information

4. The Poisson Distribution

4. The Poisson Distribution Virual Laboraories > 13. The Poisson Process > 1 2 3 4 5 6 7 4. The Poisson Disribuion The Probabiliy Densiy Funcion We have shown ha he k h arrival ime in he Poisson process has he gamma probabiliy densiy

More information

PRICE VOLATILITY ON THE USD/JPY MARKET AS A MEASURE OF INVESTORS ATTITUDE TOWARDS RISK

PRICE VOLATILITY ON THE USD/JPY MARKET AS A MEASURE OF INVESTORS ATTITUDE TOWARDS RISK QUANTITATIVE METHODS IN ECONOMICS Vol. XI, No. 1, 010, pp. 37-44 PRICE VOLATILITY ON THE USD/JPY MARKET AS A MEASURE OF INVESTORS ATTITUDE TOWARDS RISK Kaarzyna Banasiak Deparmen of Economics of Agriculure

More information

FORECASTING WATER DEMAND FOR AGRICULTURAL, INDUSTRIAL AND DOMESTIC USE IN LIBYA

FORECASTING WATER DEMAND FOR AGRICULTURAL, INDUSTRIAL AND DOMESTIC USE IN LIBYA Inernaional Review of Business Research Papers Vol.4 No. 5 Ocober-November 8 Pp. 31-48 FORECASTING WATER DEMAND FOR AGRICULTURAL, INDUSTRIAL AND DOMESTIC USE IN LIBYA Fahis F. Lawgali* This paper examines

More information

The Real Business Cycle paradigm. The RBC model emphasizes supply (technology) disturbances as the main source of

The Real Business Cycle paradigm. The RBC model emphasizes supply (technology) disturbances as the main source of Prof. Harris Dellas Advanced Macroeconomics Winer 2001/01 The Real Business Cycle paradigm The RBC model emphasizes supply (echnology) disurbances as he main source of macroeconomic flucuaions in a world

More information

Time Series Econometrics. Heteroskedasticity in Stock Return Data: Volume and Number of Trades versus GARCH Effects

Time Series Econometrics. Heteroskedasticity in Stock Return Data: Volume and Number of Trades versus GARCH Effects DEPARTMENT OF ECONOMICS Uppsala Universiy Maser Thesis Auhor: Chriser Rosén Supervisor: Lennar Berg December 007 Time Series Economerics Heeroskedasiciy in Sock Reurn Daa: Volume and Number of Trades versus

More information

MATERIALS AND METHODS

MATERIALS AND METHODS Amin e al., The Journal of Animal & Plan Sciences, 24(5): 204, Page: J. 444-45 Anim. Plan Sci. 24(5):204 ISSN: 08-708 TIME SERIES MODELING FOR FORECASTING WHEAT PRODUCTION OF PAKISTAN M. Amin, M. Amanullah

More information

Modeling and Estimation of Volatility in the Indian Stock Market

Modeling and Estimation of Volatility in the Indian Stock Market Inernaional Journal of Business and Managemen February, Modeling and Esimaion of Volailiy in he Indian Sock Marke Hojaallah Goudarzi (Corresponding auhor) Deparmen of Sudies in Commerce, Universiy of Mysore

More information

Skewness and Kurtosis Adjusted Black-Scholes Model: A Note on Hedging Performance

Skewness and Kurtosis Adjusted Black-Scholes Model: A Note on Hedging Performance Finance Leers, 003, (5), 6- Skewness and Kurosis Adjused Black-Scholes Model: A Noe on Hedging Performance Sami Vähämaa * Universiy of Vaasa, Finland Absrac his aricle invesigaes he dela hedging performance

More information

Machine Learning in Pairs Trading Strategies

Machine Learning in Pairs Trading Strategies Machine Learning in Pairs Trading Sraegies Yuxing Chen (Joseph) Deparmen of Saisics Sanford Universiy Email: osephc5@sanford.edu Weiluo Ren (David) Deparmen of Mahemaics Sanford Universiy Email: weiluo@sanford.edu

More information

DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS

DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS Hong Mao, Shanghai Second Polyechnic Universiy Krzyszof M. Osaszewski, Illinois Sae Universiy Youyu Zhang, Fudan Universiy ABSTRACT Liigaion, exper

More information

Price-to-Earnings Ratios: Growth and Discount Rates

Price-to-Earnings Ratios: Growth and Discount Rates Price-o-Earnings Raios: Growh and Discoun Raes Andrew Ang Ann F. Kaplan Professor of Business Columbia Universiy Xiaoyan Zhang Associae Professor of Finance Kranner School of Managemen, Purdue Universiy

More information

Supply chain management of consumer goods based on linear forecasting models

Supply chain management of consumer goods based on linear forecasting models Supply chain managemen of consumer goods based on linear forecasing models Parícia Ramos (paricia.ramos@inescporo.p) INESC TEC, ISCAP, Insiuo Poliécnico do Poro Rua Dr. Robero Frias, 378 4200-465, Poro,

More information

MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR

MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR The firs experimenal publicaion, which summarised pas and expeced fuure developmen of basic economic indicaors, was published by he Minisry

More information

Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach Energies 2011, 4, 1246-1257; doi:10.3390/en4081246 OPEN ACCESS energies ISSN 1996-1073 www.mdpi.com/journal/energies Aricle Forecasing Elecriciy Demand in Thailand wih an Arificial Neural Nework Approach

More information

Investor sentiment of lottery stock evidence from the Taiwan stock market

Investor sentiment of lottery stock evidence from the Taiwan stock market Invesmen Managemen and Financial Innovaions Volume 9 Issue 1 Yu-Min Wang (Taiwan) Chun-An Li (Taiwan) Chia-Fei Lin (Taiwan) Invesor senimen of loery sock evidence from he Taiwan sock marke Absrac This

More information

Dynamic Hedge Rations on Currency Futures. Bartosz Czekierda and Wei Zhang

Dynamic Hedge Rations on Currency Futures. Bartosz Czekierda and Wei Zhang Dynamic Hedge Raions on Currency Fuures Barosz Czekierda and Wei Zhang Graduae School Maser of Science in Finance Maser Degree Projec No.2010:135 Supervisor: Charles Nadeau and Joakim Weserlund Absrac

More information

Predicting Stock Volatility Using After-Hours Information: Evidence. from the NASDAQ Actively Traded Stocks

Predicting Stock Volatility Using After-Hours Information: Evidence. from the NASDAQ Actively Traded Stocks Predicing Sock Volailiy Using Afer-Hours Informaion: Evidence from he NASDAQ Acively Traded Socks Chun-Hung Chen 1 Office of he Comproller of he Currency Wei-Choun Yu 2 Winona Sae Universiy Eric Zivo 3

More information

USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES

USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES Mehme Nuri GÖMLEKSİZ Absrac Using educaion echnology in classes helps eachers realize a beer and more effecive learning. In his sudy 150 English eachers were

More information

ARCH 2013.1 Proceedings

ARCH 2013.1 Proceedings Aricle from: ARCH 213.1 Proceedings Augus 1-4, 212 Ghislain Leveille, Emmanuel Hamel A renewal model for medical malpracice Ghislain Léveillé École d acuaria Universié Laval, Québec, Canada 47h ARC Conference

More information

A dynamic probabilistic modeling of railway switches operating states

A dynamic probabilistic modeling of railway switches operating states A dynamic probabilisic modeling of railway swiches operaing saes Faicel Chamroukhi 1, Allou Samé 1, Parice Aknin 1, Marc Anoni 2 1 IFSTTAR, 2 rue de la Bue Vere, 93166 Noisy-le-Grand Cedex, France {chamroukhi,same,aknin}@ifsar.fr

More information

Time Series Analysis using In a Nutshell

Time Series Analysis using In a Nutshell 1 Time Series Analysis using In a Nushell dr. JJM J.J.M. Rijpkema Eindhoven Universiy of Technology, dep. Mahemaics & Compuer Science P.O.Box 513, 5600 MB Eindhoven, NL 2012 j.j.m.rijpkema@ue.nl Sochasic

More information

ECONOMETRIC MODELLING AND FORECASTING OF FREIGHT TRANSPORT DEMAND IN GREAT BRITAIN

ECONOMETRIC MODELLING AND FORECASTING OF FREIGHT TRANSPORT DEMAND IN GREAT BRITAIN ECONOMETRIC MODELLING AND FORECASTING OF FREIGHT TRANSPORT DEMAND IN GREAT BRITAIN Shujie Shen, Tony Fowkes, Tony Whieing and Daniel Johnson Insiue for Transpor Sudies, Universiy of Leeds, Leeds, UK, LS2

More information

4. International Parity Conditions

4. International Parity Conditions 4. Inernaional ariy ondiions 4.1 urchasing ower ariy he urchasing ower ariy ( heory is one of he early heories of exchange rae deerminaion. his heory is based on he concep ha he demand for a counry's currency

More information

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS

TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS RICHARD J. POVINELLI AND XIN FENG Deparmen of Elecrical and Compuer Engineering Marquee Universiy, P.O.

More information

A Re-Examination of the Unbiased Forward Rate Hypothesis in the Presence of Multiple Unknown Structural Breaks

A Re-Examination of the Unbiased Forward Rate Hypothesis in the Presence of Multiple Unknown Structural Breaks A Re-Examinaion of he Unbiased Forward Rae Hypohesis in he Presence of Muliple Unknown Srucural Breaks Abdulnasser Haemi-J UAE Universiy E-mail: AHaemi@uaeu.ac.ae Eduardo Roca Deparmen of Accouning, Finance

More information

Review of Middle East Economics and Finance

Review of Middle East Economics and Finance Review of Middle Eas Economics and Finance Volume 4, Number 008 Aricle 3 Transiory and Permanen Volailiy s: The Case of he Middle Eas Sock Markes Bashar Abu Zarour, Universiy of Paras Cosas P. Siriopoulos,

More information

Forecasting International Tourism Demand in Malaysia Using Box Jenkins Sarima Application

Forecasting International Tourism Demand in Malaysia Using Box Jenkins Sarima Application Souh Asian Journal of Tourism and Heriage (2010), Vol. 3, Number 2 Forecasing Inernaional Tourism Demand in Malaysia Using Box Jenins Sarima Applicaion LOGANATHAN, NANTHAKUMAR* and YAHAYA IBRAHIM** *Loganahan,

More information

Revisions to Nonfarm Payroll Employment: 1964 to 2011

Revisions to Nonfarm Payroll Employment: 1964 to 2011 Revisions o Nonfarm Payroll Employmen: 1964 o 2011 Tom Sark December 2011 Summary Over recen monhs, he Bureau of Labor Saisics (BLS) has revised upward is iniial esimaes of he monhly change in nonfarm

More information

Volatility in Returns of Islamic and Commercial Banks in Pakistan

Volatility in Returns of Islamic and Commercial Banks in Pakistan Volailiy in Reurns of Islamic and Commercial Banks in Pakisan Muhammad Iqbal Non-Linear Time Series Analysis Prof. Rober Kuns Deparmen of Economic, Universiy of Vienna, Vienna, Ausria Inroducion Islamic

More information

5 Autoregressive-Moving-Average Modeling

5 Autoregressive-Moving-Average Modeling 5 Auoregressive-Moving-Average Modeling 5. Purpose. Auoregressive-moving-average (ARMA) models are mahemaical models of he persisence, or auocorrelaion, in a ime series. ARMA models are widely used in

More information